Although research relating to the urban heat island (UHI) phenomenon has been significantly increasing in recent years, there is still a lack of a continuous and clear recognition of the potential gradient effect on the UHI—landscape relationship within large urbanized regions. In this study, we chose the Beijing-Tianjin-Hebei (BTH) region, which is a large scaled urban agglomeration in China, as the case study area. We examined the causal relationship between the LST variation and underlying surface characteristics using multi-temporal land cover and summer average land surface temperature (LST) data as the analyzed variables. This study then further discussed the modeling performance when quantifying their relationship from a spatial gradient perspective (the grid size ranged from 6 to 24 km), by comparing the ordinary least squares (OLS) and geographically weighted regression (GWR) methods. The results indicate that: (1) both the OLS and GWR analysis confirmed that the composition of built-up land contributes as an essential factor that is responsible for the UHI phenomenon in a large urban agglomeration region; (2) for the OLS, the modeled relationship between the LST and its drive factor showed a significant spatial gradient effect, changing with different spatial analysis grids; and, (3) in contrast, using the GWR model revealed a considerably robust and better performance for accommodating the spatial non-stationarity with a lower scale dependence than that of the OLS model. This study highlights the significant spatial heterogeneity that is related to the UHI effect in large-extent urban agglomeration areas, and it suggests that the potential gradient effect and uncertainty induced by different spatial scale and methodology usage should be considered when modeling the UHI effect with urbanization. This would supplement current UHI study and be beneficial for deepening the cognition and enlightenment of landscape planning for UHI regulation.

Clarifying the spatiotemporal changes in the supply and demand relationship of ecosystem services (ESs) is essential for optimizing ESs management. However, several studies have reported the ESs supply and demand risk in complex mountainous areas. In this study, we quantitatively analyzed the spatiotemporal variation in ESs supply, demand, and their trade-off and synergy, including water yield, soil conservation, and food provision in the Bailongjiang watershed (BLJW) in western China. The results showed that the total supply and demand of water-yield and soil-conservation services rose with a surplus from 2002 to 2018, except for food provision. A high value characterizes the water-yield and soil-conservation supply in the south, but there are low values in the east BLJW. The spatial distribution of water and food supply–demand featured a high demand in the subareas with population aggregation. Soil-conservation demand is high in the northwest and south of Wudu. The dominant spatial matching type of supply and demand in water yield was a high supply with a low demand. Soil conservation was associated with a low supply and low demand, and food provision with a high supply and increased demand. A synergy existed between water yield and soil conservation. Trade-offs existed between water yield, food provision, and soil conservation. The spatial distribution of trade-off intensity showed distinctive patterns. The supply–demand ratio of WY and SC decreased with the increasing trade-off intensity. This study comprehensively considers ES and supply–demand conflicts, thus providing a new perspective and approach for enhancing ecosystem services and high-quality regional development.